MGMT Gene Promoter Methylation Analysis by Pyrosequencing of Brain Tumour

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1 The Korean Journal of Pathology 2011; 45: MGMT Gene Promoter Methylation Analysis by Pyrosequencing of Brain Tumour Young Zoon Kim Young Jin Song 1 Ki Uk Kim 1 Dae Cheol Kim 2 Department of Neurosurgery and Division of Neurooncology, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon; Departments of 1 Neurosurgery and 2 Pathology, Dong-A University College of Medicine, Busan, Korea Received: May 22, 2011 Accepted: August 30, 2011 Corresponding Author Dae Cheol Kim, M.D. Department of Pathology, Dong-A University College of Medicine, Dongdaesin-dong 3-ga, Seo-gu, Busan , Korea Tel: Fax: freehand@dau.ac.kr *This work was supported by the Dong-A University research fund. Background: The aim of this study was to determine whether pyrosequencing (PSQ) might be useful to achieve O6-methyl guanine methyltransferase (MGMT) promoter methylation using 1- to 13-year-old archival tissues as a clinical biomarker in routine practice. Methods: The study included 141 formalin-fixed paraffin-embedded (FFPE) glial tumors from the archives of the Pathology Department from Results: The average percentage of methylation (MP) of the 141 cases was 14.0± 16.8%, and methylated cases were 32.3± 14.9%. The average MP of each year did not show a linear increasing or decreasing pattern according to the age of the FFPE block (p= 0.771). The average MP of methylated glioblastomas was 35.8±14.7%, 31.8±15.5% for anaplastic astrocytomas, and 22.4±15.1% for astrocytoma. A tendency was observed toward an increasing pattern of average MP with World Health Organization (WHO) grade (p= 0.063) in astrocytic tumors. A correlation was observed between average MP and WHO grade (p= 0.038) and a bimodal distribution was observed between the methylated and unmethylated cases, using a 9% cut-off value (p< 0.001). Conclusions: The results showed that a quantitative approach for MGMT promoter methylation yielded a 100% success rate for FFPE tissues from archives. PSQ can be used in a retrospective trial, but the cut-off value and calculation method should be further validated. Key Words: Glioma; MGMT; Pyrosequencing; Biomarker; Methylation Gliomas are the most common type of primary brain tumors, and glioblastoma (GBM) is the most frequent malignant brain tumor, accounting for approximately 12-15% of all intracranial neoplasms and 60-75% of astrocytic tumors. An analysis of 5,692 patients diagnosed with primary central nervous system (CNS) tumors in 2005 in the Republic of Korea showed that GBM accounted for 5.9% of all CNS tumors and 30.4% of all neuroepithelial tumors. 1 Although the overall incidence rate of primary brain tumors is very low among all human cancers, GBMs are a highly invasive and aggressively growing tumor that responds poorly to radiation therapy and most forms of chemotherapy. The prognosis is correspondingly poor, with most patients dying within 1 year after diagnosis. Compared to treatment of other types of cancer, treatment for GBM is very difficult, because drugs must cross the blood brain barrier to reach the tumor and avoid protein efflux. The mainstream treatment for GBM is surgical removal where possible, followed by radiotherapy. Hegi et al. 2 investigated the O6-methyl guanine methyltransferase (MGMT) promoter methylation status in a large cohort of patients with GBM by comparing patients who received radiotherapy alone or radiotherapy combined with temozolomide (TMZ) with patients with methylated MGMT who benefitted from adding TMZ. A clinical trial (EORTC 26981/22981 and NCIC CE.3) of concurrent TMZ and radiotherapy followed by adjuvant TMZ for newly diagnosed patients with GBM showed a considerable advance, achieving a median survival of 14.6 months and a 2-year survival of 26%. 3 TMZ is an alkylating chemotherapeutic agent that causes DNA damage by transferring alkyl groups at several sites within DNA, including the O6 position of guanine. The MGMT gene plays a fundamental role maintaining genomic integrity by encoding for a DNA repair protein that removes alkyl groups from O6- guanine. 4 Epigenetic silencing by promoter methylation results in decreased MGMT expression and correlates with improved survival in patients with glioma treated with alkylating agents. 5 Although MGMT promoter methylation is used as a prognostic/predictive marker in patients with GBM, no consensus exists on the method to be applied. Methylation-specific poly- 455

2 456 Young Zoon Kim Young Jin Song Ki Uk Kim, et al. merase chain reaction (PCR) (MSP) has been widely used, and this method enables cost-efficient analysis of MGMT promoter methylation. However, it is not a quantitative method and has the risk of false-positive or false-negative results, particularly when the DNA quality and/or quantity are low. In the EORTC 26981/22981 and NCIC CE.3 trials, Hegi et al. 2 only collected data from 67% of the samples analyzed, representing 36% of cases from their archives. The success rate of MSP on formalinfixed paraffin-embedded (FFPE) tumor samples was highly variable and the median success rate was 75.0% (range, 0 to 100%). They recommended that diagnostic MGMT testing requires sufficient and optimally preserved tumor tissue such as cryopreserved tumor specimens; thus, avoiding fixation-related deterioration of tumor DNA quality. An alternative technique to overcome the problem with MSP is pyrosequencing (PSQ), which is based on the sequencing-by-synthesis principle and involves a simple technique for accurate and quantitative analysis of DNA sequences. PCR followed by PSQ is one such sensitive, highly reproducible, and cost-effective method 6 for DNA methylation analyses. It provides absolute quantitative information based on each interrogated CpG site, which is not possible with most other methods. Additionally, unlike other methods, the assay design allows inclusion of internal controls to address inaccuracies resulting from incomplete bisulfite conversion. Mikeska et al. 7 compared and optimized three quantitative MGMT promoter methylation techniques and concluded that the PSQ assay provides the most accurate and is robust when applied to archival samples including those of GBM. They 7 described a comparison of the programs obtained from matched snap-frozen and FFPE tissues, and the overall methylation score led to the same molecular diagnostic decision in all cases. The objective of this study was to determine whether PSQ might be useful to determine MGMT promoter methylation status using 1- to 13-year-old archival tissue samples of glial tumors as a clinical biomarker in routine practice. We discuss our results with applicability to molecular diagnostics. Sample selection MATERIALS AND METHODS The study set included FFPE brain tumor tissue from 162 patients at the Department of Pathology archives of Dong-A University Medical Center from 1997 to 2010, of which all were diagnosed with glial tumors. All patients underwent surgical removal or biopsy sampling of their tumors. Adjuvant conventional radiotherapy and/or chemotherapy were performed after the pathological diagnosis in all patients. All hematoxylin and eosin slides were reviewed (World Health Organization Classification 2007) and selected by two pathologists without any information regarding clinical and pathological parameters. Tumors were excluded if the tissue was almost entirely necrotized or tumor volume of the section was <80%. 7 Finally, 141 patients were selected. This study was reviewed and approved by the Dong-A University Ethical Committee ( ). DNA extraction and bisulfite conversion Genomic DNA was extracted from three (10 µm thickness) slices of FFPE material using the QIAamp DNA FFPE extraction kit and the QIAcube automated DNA extraction machine (Qiagen, Hilden, Germany) and quantified by UV absorption (Nanodrop, Thermo Scientific, Wilmington, DE, USA), typically yielding a total >1 µg of gdna per specimen. gdna (200 ng) was used in the bisulfite conversion reactions in which unmethylated cytosine was converted to uracil with the EpiTect bisulfite kit (Qiagen), according to the manufacturer s instructions. In short, DNA was mixed with water. The DNA was protected by the buffer and bisulfite mix, and the conversion was run on an ABI 2727 Thermocycler (Applied Biosystems, Foster City, CA, USA) under the recommended cycle conditions. Converted DNA was purified and eluted in two steps in a total of 40 µl buffer EB and further diluted into 20 µl aliquots of 1,000 cell-equivalents/µl (the cell calculations assumed 6 pg DNA per diploid cell). PCR and PSQ Primer sets with one biotin-labeled primer were used to amplify the above bisulfite-converted DNA samples. The Pyro- Mark Q96 CpG MGMT kit 8,9 (Ensembl ID: OTTHUMT ) (Qiagen) is available as a ready-to-use research kit, and this kit was able to detect the level of methylation at exon 1 positions of the MGMT gene, containing 5 CpGs. A cytosine not followed by a guanine, which is not methylated, served as an internal control and was programmed automatically by the PSQ96MA 2.1 software (Biotage, Uppsala, Sweden) to verify the efficiency of bisulfite conversion. Theoretically, the internal control must be zero, because all cytosines not followed by a guanine are converted to uracil during bisulfite conversion, then, uracil is converted to thymine after PCR. Usually <5%

3 MGMT Methylation Analysis by Pyrosequencing as a Novel Method 457 was an acceptable value for the internal control according to the manufacturer s protocol. If the value of the internal control was >5%, all procedures were repeated again (from bisulfite conversion to PSQ). PCR was performed using a converted gdna equivalent of approximately 5,000 cells and using the PyroMark PCR kit (Qiagen). Briefly, 12.5 µl master mix, 2.5 µl Coral red, 5 pmol of each primer, 7 µl of water, and 2 µl sample were mixed for each reaction and run under the following thermal cycling conditions: 95 C for 15 minutes and then 45 cycles for 30 seconds at 94 C; 30 seconds at the optimized primer-specific annealing temperature; 30 seconds at 72 C, and a final extension for 10 minutes at 72 C. The correct amplified DNA was confirmed by electrophoresis on a 2% low melting point agarose gel (Sigma- Aldrich, Steinheim, Germany) in tris-borate-edta buffer. A standard PSQ sample preparation protocol was applied. 10 Streptavidin beads (3 µl; GE Healthcare, Buckinghamshire, UK), 37 µl PyroMark binding buffer (Qiagen, Hilden, Germany), 20 µl PCR product, and 20 µl water were mixed and incubated for 10 minutes on a shaking table at 1,300 rpm. Amplicons were separated, denatured, washed, and added to 45 µl annealing buffer containing 0.33 µm of PSQ primer using the Biotage Q96 Vacuum Workstation. Primer annealing was performed by incubating the samples at 80 C for 2 minutes, which were allowed to cool to room temperature prior to PSQ. PyroGold reagents were used for the PSQ reaction, and the signal was analyzed using the PSQ 96MA System (Biotaqe, Uppsala, Sweden). Target CpGs were evaluated by PSQ96MA 2.1 instrument software (Biotaqe, Uppsala, Sweden) which converts the pyrograms to numerical values for peak heights and calculates the proportion of methylation at each base as a C/T ratio. Methylation values 5% were considered potential background noise signals of questionable significance, as shown in other studies Unmethylated (300 ng; Qiagen, Hilden, Germany) and hypermethylated DNA (Millipore, Billerica, MA, USA) were used as standard controls, and bisulfite was converted as described above. Data analyses The main analyses converted individual C/T ratio data into mean values of the five CpGs analyzed in a gene segment. The percentage of the mean value of five CpGs were considered methylated if the percentage was >9%. 14 The chi-square test was used for parametric comparisons to analyze associations between markers. Differences in the averages between groups were tested by a t-test or analysis of variance. Significance was accepted at p-values<0.05. Statistical analyses were performed with SPSS ver (SPSS Inc., Chicago, IL, USA). Patient characteristics RESULTS In total, 141 patients were analyzed by the PSQ method, and Table 1 shows the overall details of the data set. The age of the patients ranged from 1 to 77 years (mean age, 43.4 years). Seventy-seven cases were males (mean age, 44.8 years), and 64 were females (mean age, 41.8 years). The data set showed a male predominance, and females tended to be diagnosed at a younger age than males; however it was not statistically significant. Seventy-five cases (53.2%) were diagnosed with GBM (mean age, 51.1 years), 22 cases (15.6%) were diagnosed with anaplastic astrocytoma (AA) (mean age, 47.0 years) and 19 cases (13.5%) were diagnosed with grade II astrocytoma (mean age, 33.9 years). The mean age of patients with an astrocytic tumor increased significantly according to the World Health Organization (WHO) grading system (p<0.01). Nine patients (6.4%) were diagnosed with anaplastic oligodendroglioma (AO) (mean age, 34.5 years) and two patients (1.4%) were diagnosed with oligodendroglio- Table 1. Clinicopathological data of the 141 glial tumor cases No. of cases Sex Male Female Age (yr) > Diagnosis Glioblastoma Anaplastic astrocytoma Astrocytoma Anaplastic oligodendroglioma Oligodendroglioma Pilocytic astrocytoma ETC a WHO Grade Grade Grade Grade Grade S tatus of methylation Methylated Unmethylated Total a Three ependymomas, a juvenile pilomyxoid astrocytoma, a dysembryoplastic neuroepithelial tumor, an infantile desmoplastic astrocytoma, a pleomorphic xanthoastrocytoma, and a primitive neuroectodermal tumor. ETC, et cetera; WHO, World Health Organization. %

4 458 Young Zoon Kim Young Jin Song Ki Uk Kim, et al. T: 79.9% C: 20.1% T: 80.0% T: 80.5% C: 20.0% C: 19.5% T: 83.0% T: 79.7% T: 100.0% C: 17.0% C: 20.3% C: 0.0% T: 100.0% C: 0.0% T: 100.0% T: 100.0% C: 0.0% C: 0.0% T: 100.0% C: 0.0% T: 100.0% T: 100.0% C: 0.0% C: 0.0% E S A T C A G T T G T C A G T C T G A T C A G T C A G T C G A A E S A T C A G T T G T C A G T C T G A T C A G T C A G T C G A B Fig. 1. Two representative glioblastoma pyrograms are shown. Five consecutive positions are analyzed for CpGs and the last one is an internal control for bisulfite treatment. Each C peak in a yellow background represents the methylation percentage for each CpG. (A) Methylated glioblastoma. (B) Unmethylated glioblastoma. Table 2. Average percentage of methylation in total and the methylated cases from 1997 to 2010 Year of block No. of cases (%) MP average (%) SD (%) ma (mean age, 40.5 years). Seven patients (5.0%) had pilocytic astrocytoma (PA) (mean age, 17.7 years). Three cases were an ependymoma, a juvenile pilomyxoid astrocytoma, and a dysembryoplastic neuroepithelial tumor. Infantile desmoplastic astrocytoma, pleomorphic xanthoastrocytoma, and a primitive neuroectodermal tumor were included in the et cetera (ETC) category. MGMT promoter methylation analysis No. of methylated cases (%) MP average (%) SD (%) (12) (17.6) (3) (75.0) (6) (37.5) (7) (40.0) (7) (30.0) (8) (45.5) (4) (40.0) (6) (44.4) (6) (22.2) (7) (40.0) (11) (37.5) (5) (42.9) (9) (30.8) (9) (50.0) Total (%) 141 (100) (36.9) MP average, average percentage of methylation; SD, standard deviation. not show a increasing or decreasing linear pattern according to the age of the FFPE block. Thirty-one (41.3%) of 75 GBMs were methylated. The average MPs of the methylated and unmethylated cases were 35.8± 14.7% and 3.2±1.8%, respectively (p<0.001). Eight (36.4%) of 22 AA were methylated, and the average MP of AA was 31.8 ±15.5%. Eight (42.1%) of 19 astrocytomas were methylated, and the average MP was 22.4±15.1%. We observed a tendency for an increasing pattern of average MP with WHO grade (p= 0.063) in astrocytic tumors. Four of seven cases (57.4%) with AO were methylated, and the average MPs were 30.0±8.5% and 4.7±1.1% in the methylated and unmethylated cases, respectively. One oligodendroglioma was methylated, and 20.0 ±0.0% was the average MP. Five of eight cases (75.0%) of oligodendroglial tumor were methylated, and the average MPs of the methylated and unmethylated oligodendroglial tumors were 28.0±8.1% and 4.7±1.2%, respectively (p=0.024). Nine PAs were unmethylated, and the average MP was 3.0±1.3%. The ETC group was unmethylated as well with an average MP of 3.8±2.1% (Table 3). Table 4 shows the overall MPs of methylated glial tumors according to WHO grade. Grade 1 tumors were entirely unmethylated. We observed a correlation between average MP and WHO grade (p=0.038) and a bimodal pattern, which divided the methylated and unmethylated populations clearly using a 9% cut-off value (p<0.001). PSQ data were obtained from all 141 samples. Fig. 1 shows the pyrograms, representing cases of methylated and unmethylated GBM. Table 2 shows the average methylation percentages (MPs) for all cases and the averages of the methylated cases for 13 years by year. The mean of all cases was 14.0±16.8%, and that of methylated cases was 32.3±14.9%. The MP values for each year were not significantly different (p=0.771) and did DISCUSSION Locus-specific hypermethylation, mostly at the CpG island (CGI) promoters, is frequent in patients with GBM. CGIs are regions of ~500 bp to 1 kb in which CpG nucleotides are approximately five times more abundant compared to the rest of the genome. 15 CGI promoter hypermethylation occurs at genes

5 MGMT Methylation Analysis by Pyrosequencing as a Novel Method 459 Table 3. Summary of the average methylation percentage of methylated and unmethylated cases, categorized by diagnosis Methylated with diverse functions related to tumorigenesis and tumor progression in patients with GBM, including cell cycle regulation, DNA repair, apoptosis, angiogenesis, invasion, and drug resistance. Genes involved in invasion and metastasis of gliomas can also be affected by promoter hypermethylation. Promoter hypermethylation can modulate sensitivity to drugs and radiotherapy in patients with GBM. One of the best known examples is MGMT promoter methylation and the response to DNA alkylating agents. MGMT encodes a DNA repair protein that removes alkyl adducts at the O6 position of guanine. MGMT expression protects normal cells from carcinogens; however, it can also protect cancer cells from chemotherapeutic alkylating agents. An association between MGMT promoter methylation status and clinical outcome of patients with GBM has been shown in many studies. Based on these results, MGMT promoter methylation is considered a promising molecular factor predictive of the chemotherapy response and longer survival in patients with GBM. Hegi et al. 2 reported that 45% of GBMs are methylated in his randomized trial, and that the median success rate of MSP was 75% in FFPE samples. Our PSQ success rate was 100% on 141 samples from 1- to 13-year-old archive specimens, and 41.3% of the GBMs were methylated. Both methylation frequencies were very similar and, recently, Lee et al. 16 showed that Unmethylated No. of cases (%) Mean±SD (%) No. of cases (%) Mean±SD (%) Total (%) Glioblastoma 31 (41.3) 35.8± (58.7) 3.2± (100) < Anaplastic astrocytoma 8 (36.4) 31.8± (63.6) 3.3± (100) < Astrocytoma 8 (42.1) 22.4± (57.9) 3.4± (100) Anaplastic oligodendroglioma 4 (57.1) 30.0±8.5 3 (42.9) 4.7±1.1 7 (100) Oligodendroglioma 1 (100) 20.0± (100) Pilocytic astrocytoma (100) 3.0±1.3 9 (100) ETC a (100) 2.7±1.1 7 (100) Total ± ±1.9 a Three ependymomas, juvenile pilomyxoid astrocytoma, a dysembryoplastic neuroepithelial tumor, an infantile desmoplastic astrocytoma, a pleomorphic xanthoastrocytoma, and a primitive neuroectodermal tumor. SD, standard deviation; ETC, et cetera. Table 4. Average methylation percentage of all cases and the methylated cases according to WHO grade WHO grade No. of total cases Mean±SD (%) No. of methylated cases Mean±SD (%) Grade ± Grade ± ±14.1 Grade ± ±13.2 Grade ± ±14.7 Total ± ±14.9 WHO, World Health Organization; SD, standard deviation. p-value 44.4% of GBMs are methylated of 27 cases of GBM. Overall, 36.9% of all gliomas were methylated, ranging from 36.4% to 57.1% in our study. Based on our results and several researcher s data, 40-50% of GBMs are potentially methylated, which might be of benefit during treatment with alkylating agents. We demonstrated PSQ results from 1- to 13-year-old archive specimens. The percentage of methylation over the years were evenly distributed and no increasing or decreasing pattern of MP with specimen age was observed. This might be a huge improvement in the success rate when compared with Hegi et al. 2 Dunn et al. 14 obtained 264 of 287 tumor samples from 121 cases by PSQ. Failure may have occurred due to the small sample size (<1 mm 3 ) with low DNA yield or due to poor DNA integrity in the FFPE samples. Despite some failures, the PSQ data were reproducible and showed a good correlation between duplicate PCR reactions from the same bisulfite modification and between two independent bisulfite modifications of the same DNA extract. 14 Therefore, the PCR followed by the PSQ method is a stable technique and produces consistent data. These results support the need for a large nationwide retrospective trial to evaluate MGMT promoter methylation status of old archives from multi-institutions. The average percentage of methylation in the methylated cases increased significantly with WHO grade, suggesting that MP increases when tumors progress and that methylation status and MP must be analyzed together. Some cases with a high MP in grade II astrocytomas or a low percentage in GBMs may have different tumor progression behavior and responsiveness to alkylating agents. Dunn et al. 14 showed an interesting clustering analysis based on the extent of methylation. Progressionfree survival was significantly different between low (9%<MP 29%) and high (>29%) methylation groups of GBM and between high methylated and unmethylated cases. Log-rank tests showed significant differences in overall survival between un-

6 460 Young Zoon Kim Young Jin Song Ki Uk Kim, et al. methylated and methylated groups and between cases with low vs high methylation. This result suggested that qualitative and quantitative data should be simultaneously obtained from the MGMT methylation analysis to expect progression-free survival, overall survival, or a prediction of chemo-responsiveness in clinical practice. Alonso et al. 17 reported aberrant promoter methylation of multiple genes, including MGMT in oligodendrogliomas and ependymomas, using MSP. According to their data, MGMT presented with the highest methylation frequency among oligodendroglial tumors, 80% (33/41), showing similar rates in the three groups (oligodendroglioma, AO, and oligoastrocytoma). A significant MGMT promoter methylation rate (28%; 2/7) was found in grade II and III ependymomas. Everhard et al. 18 evaluated the frequency of MGMT promoter methylation in low grade gliomas and showed that 11% of grade II astrocytomas, 62% of grade II oligodendrogliomas, and 27% of grade II oligoastrocytomas were methylated by MSP. In our series, 42% of grade II astrocytomas and a case of oligodendroglioma were methylated. A large difference in methylation status, such as 11% and 80% by MSP and 42% by PSQ, was observed. A few clinical trials of low grade gliomas are ongoing to determine the status of MGMT promoter methylation and the role of TMZ in tumor management. The relevant genes on 1p and 19q are still unidentified, and it is unclear whether alterations in one or more genes on these chromosome arms, or rather in completely different chromosomal locations, may account for the clinically less aggressive behavior of 1p/19q deleted tumors. The observation that MGMT promoter hypermethylation is common in oligodendrogliomas with losses on 1p and 19q may point to at least one possible mechanism contributing to the chemosensitivity of these tumors. 19 In our study, seven PAs were all unmethylated. PAs can be considered a grade I glial tumor, and PAs are frequently unmethylated; however, sufficient references to PA methylation status, compared with our results are not available yet. Our three grade II ependymomas were unmethylated. In contrast, Koos et al. 20 analyzed 142 ependymal tumors and showed that 27% of ependymal tumors were methylated by MSP, and that methylation of the MGMT promoter region was significantly less frequent when compared with malignant astrocytic gliomas. Nicholson et al. 21 reported that the majority of ependymomas respond poorly to TMZ treatment. It might be too early to determine the usefulness of MGMT promoter methylation status for low grade gliomas, so further comprehensive study will be needed. Several methods to determine promoter methylation have been described, including the use of restriction enzymes 22 or genomic bisulfite sequencing. 23 The overwhelming majority of published data uses MSP following bisulfite treatment. 24 MSP is highly sensitive and has been used widely in this context. 24,25 However, as there are no inbuilt measures of the adequacy of bisulfite treatment, the possibility of false positives due to inadequate conversion of non-methylated cytosine to uracil exists. Another potential source of false positives is mis-priming, and this may be a greater problem when high numbers of PCR cycles or nested primers are used. Previously described methods for controlling mis-priming include re-analysis by methylationsensitive restriction enzymes 26 or subsequent bisulfite DNA sequencing. 27 An accurate quantitative analysis is very important for a DNA methylation analysis, and MSP has many weaknesses in this regard. One of the major issues with MSP is the use of relative quantification by means of an external control using a different PCR for the control gene. The accuracy and reproducibility of this approach has still not been adequately addressed for the large diversity of genes. Development of DNA methylation risk prediction panels based on diverse genes will be required to develop and optimize an accurate and reproducible method. Cut-off values for the percentage methylation might be one of the critical issues to determine methylation status using PSQ analysis. Mikeska et al. 7 reported that unmethylated tumor samples and control samples show ratios of <10% at all positions with a small standard deviation and suggested a Scorepy15 formula to separate unmethylated and methylated cases by employing the percentage values of four specified CpGs. Dunn et al. 14 stated that GBMs should be considered methylated if they have 9% average methylation and unmethylated cases should have an average methylation<9% in all samples. Karayan-Tapon et al. 9 analyzed methylation status in patients with GBM by five different methods. They used the PyroMark MGMT TM kit, containing five CpGs, which overlapped with the sequence of Mikeska et al. 7 for analysis. Patients with a CpG4 percentage methylation greater than the median value (7.9%) had highly significant longer overall survival than patients with mean methylation for the five CpGs >8% (median value). Three researchers have used different cut-off values of >10%, 9%, and 8%, which look very similar, but cause a problem if a case has a borderline value such as 8.5% or 9.5% which could represent methylated or unmethylated status. Our study adopted a cut-off value >9%, and four case values were very close to 9%. Two were AAs, with cut-offs of 8.2% and 8.5%, respectively, and considered unmethylated status and the remaining were GBMs, with

7 MGMT Methylation Analysis by Pyrosequencing as a Novel Method % and 9.9% cut-offs, were categorized as methylated. Dunn et al. 14 reported a 3.2±2.89% MP for control non-neoplastic brain samples and 51.2% for GBM and average methylation across all CpGs in at least one clinical sample greater than that of non-neoplastic brain ( 9%) were classified as methylated. Mikeska et al. 7 estimated methylation status based on logistic regression of a full validation dataset to calculate optimal separation between unmethylated and methylated cases. These are current limitations to the PSQ method, including a lack of consensus on how the data should be interpreted. In clinical practice, an optimal threshold to convert percentage methylation into a qualitative score must be established as a binary classification for clinical testing. Another issue for MGMT promoter methylation analysis is the relevant CpG sites for methylation status. The MGMT promoter methylation pattern is very heterogeneous from tumor to tumor, and the CpG sites that need to be methylated to silence transcription and provide a favorable outcome have not been established. Several studies have investigated the methylation status at individual CpGs within MGMT CGI and compared them with gene expression. Watts et al. 28 studied the methylation status of 108 CpGs across MGMT CGI using bisulfite sequencing, and they identified three distinct regions within CGI where high methylation levels were found but only in the MGMT non-expressing cell line. Recently, Malley et al. 29 reviewed a distinct region of the MGMT CGI for transcriptional regulation. Watt s and Malley s regions roughly overlapped with CpG1-25, differentially methylated region (DMR) 1 and 2. 28,29 They 29 found that DMR2 is always methylated when DMR1 is methylated. These results indicated that while both DMR1 and DMR2 may be important for promoter activity, DMR2 alone is practically sufficient for assessing MGMT CGI methylation during clinical testing. They concluded that at least several specific CpGs within DMR2 play an important role in MGMT CGI promoter activity; therefore, DMR2 appears to be the optimal target for clinical MGMT promoter methylation testing. Karayan-Tapon et al. 9 assessed MGMT promoter methylation status by five different methods including PSQ and his PSQ primer sets included 5 CpGs in DMR2 region, which were used in this study. They concluded that PSQ predicts overall survival well in patients initially treated with radiotherapy plus TMZ using FFPE samples. To date, MGMT methylation analysis is one of the most recommended molecular assays in clinical neuro-oncology. Due to lack of therapeutic alternatives, MGMT evaluation is only currently essential for clinical trials, although that is likely to change once effective alternative therapies are identified. A range of new methodologies are available for MGMT testing that potentially allow higher levels of sensitivity, specificity, robustness, and reproducibility, and PSQ is one of the promising techniques for MGMT evaluation in daily practice. REFERENCES 1. Lee CH, Jung KW, Yoo H, Park S, Lee SH. Epidemiology of primary brain and central nervous system tumors in Korea. J Korean Neurosurg Soc 2010; 48: Hegi ME, Diserens AC, Gorlia T, et al. MGMT gene silencing and benefit from temozolomide in glioblastoma. N Engl J Med 2005; 352: Stupp R, Mason WP, van den Bent MJ, et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 2005; 352: Verbeek B, Southgate TD, Gilham DE, Margison GP. O6-Methylguanine-DNA methyltransferase inactivation and chemotherapy. Br Med Bull 2008; 85: Esteller M, Garcia-Foncillas J, Andion E, et al. Inactivation of the DNA-repair gene MGMT and the clinical response of gliomas to alkylating agents. N Engl J Med 2000; 343: Marsh S. Pyrosequencing applications. Methods Mol Biol 2007; 373: Mikeska T, Bock C, El-Maarri O, et al. Optimization of quantitative MGMT promoter methylation analysis using pyrosequencing and combined bisulfite restriction analysis. J Mol Diagn 2007; 9: Etcheverry A, Aubry M, de Tayrac M, et al. DNA methylation in glioblastoma: impact on gene expression and clinical outcome. BMC Genomics 2010; 11: Karayan-Tapon L, Quillien V, Guilhot J, et al. Prognostic value of O6-methylguanine-DNA methyltransferase status in glioblastoma patients, assessed by five different methods. J Neurooncol 2010; 97: Tost J, Gut IG. DNA methylation analysis by pyrosequencing. Nat Protoc 2007; 2: Brakensiek K, Wingen LU, Länger F, Kreipe H, Lehmann U. Quantitative high-resolution CpG island mapping with Pyrosequencing reveals disease-specific methylation patterns of the CDKN2B gene in myelodysplastic syndrome and myeloid leukemia. Clin Chem 2007; 53: Jones AV, Kreil S, Zoi K, et al. Widespread occurrence of the JAK2 V617F mutation in chronic myeloproliferative disorders. Blood 2005; 106:

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